生物多样性 ›› 2019, Vol. 27 ›› Issue (3): 243-248.doi: 10.17520/biods.2018327

• 野生动物红外相机数据分析专题 • 上一篇    下一篇

物种相对多度指数在红外相机数据分析中的应用及局限

陈立军1, 肖文宏1, 肖治术1, 2, *()   

  1. 1 中国科学院动物研究所农业虫害鼠害综合治理研究国家重点实验室, 北京 100101
    2 中国科学院大学, 北京 100049
  • 收稿日期:2018-12-12 接受日期:2019-04-11 出版日期:2019-03-20
  • 通讯作者: 肖治术 E-mail:xiaozs@ioz.ac.cn
  • 基金项目:
    国家重点研发项目(2017YFC0503802);区域生物多样性综合监测技术与规范研究;中央林业改革发展资金;中国科学院生物多样性监测与研究网络兽类多样性监测网运行经费;中国博士后科学基金(2017M620905)

Limitations of relative abundance indices calculated from camera-trapping data

Chen Lijun1, Xiao Wenhong1, Xiao Zhishu1, 2, *()   

  1. 1 State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101
    2 University of Chinese Academy of Sciences, Beijing 100049
  • Received:2018-12-12 Accepted:2019-04-11 Online:2019-03-20
  • Contact: Xiao Zhishu E-mail:xiaozs@ioz.ac.cn

多度是衡量物种种群数量的参数之一, 多度的动态及其影响因素是种群生态学研究的经典问题。物种相对多度指数(relative abundance index, RAI)作为一种简单、便利的指标, 广泛应用于动物本底清查中。但RAI易受物种自身特征、探测率和环境因素的影响, 需要结合其他物种数量分析方法, 以验证其与种群大小的相关性。随着红外相机技术在野生动物调查中的广泛应用, 用红外相机数据估计动物种群数量的研究越来越多。目前, 基于红外相机数据计算RAI的方法有多种, 不同计算方法和应用范围存在差异, 亟需对现有方法和应用进行梳理。本文综述了根据红外相机数据计算物种相对多度的4种主要方法: (1)拍摄一张有效照片所需要的天数; (2)基于单位调查强度的物种拍摄率; (3)每个位点每天的物种拍摄率; (4)某一物种的照片数占所有物种的比例。总结了我国野生动物监测调查中采用红外相机方法计算RAI的应用现状。国内的研究主要采用第2种和第4种计算方法, 其中约72.5%的研究论文应用第2种计算方法, 而第4种方法一般适用于群落中的物种组成比较。我们建议根据红外相机数据计算RAI时尽量使用第2种计算方法, 这有助于研究或管理人员对不同研究中的物种RAI进行比较分析。

关键词: 种群数量调查, 相对多度指数, 红外相机, 物种编目

Abundance is an important parameter used to estimate the population size of various wildlife species. With the growing application of camera-traps (movement or heat activated) to monitoring wildlife, the relative abundance index (RAI) has become one of the most popular indicators of population abundance for inventories and assessment. Despite a simple and convenient indicator of population size, RAI obtained from camera-trapping data can be greatly affected by many factors such as species traits, detection rates and environmental factors. Therefore, we need verify the correlation between RAI and population density prior to its general application. So far, several types of RAIs have been developed based on camera-trapping data, and it is critical to compare these RAI indices and their applications. In this paper, we summarized the methods calculating RAI with camera-trapping data and reviewed their applications in wildlife monitoring and inventories in China. Four main types of RAIs were identified including (1) the number of days when one animal is photographed, (2) the number of photographs of focal species per 100 trap days, (3) the number of photographs of focal species per trap day, and (4) the proportion of photos from the focal species compared to all photos of all animals. Among them, the second RAI type is the most widely used (72.5%) in wildlife monitoring and inventories in China, and the fourth RAI type is used to compare species components in communities. Consequently, we recommend the second RAI type for estimating population abundance in particular when camera-trapping data are used for broad-scale comparisons over different spatial and temporal scales.

Key words: population size estimation, relative abundance index, camera-trapping, species monitoring and inventory

图1

我国基于红外相机数据计算相对多度指数(RAI)的编目论文统计分析(1997-2018)。(A)不同年份发表关于RAI的编目论文总数(N = 109); (B)不同RAI类型的文章比例, 以单位抽样时间内所拍摄的独立有效照片数来获得RAI_2 (N = 79), 包括以1,000 h为单位的论文(1000/Th, N = 4)、以1,000 d为单位的论文(1000/Td, N = 13)、以100 d为单位的论文(100/Td, N = 60)和以1 d为单位的论文(100%/Td, N = 2)等4种亚类型; 另一种则主要分析调查区域内每个物种占所有独立有效照片数的比例(N = 30), 包括每100或1,000张独立有效照片中的物种照片数(100/Np, N = 18)和物种的独立有效照片数占所有物种独立有效照片总数的比例(100%/Np, N = 12)。"

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